Faster and More Resilient Supply Chains for the New Norm

Since 2018, most probably because of the pandemic, the pace of business has changed by an order of magnitude. Supply chain planning processes have sped up from quarterly to monthly and from monthly to weekly. As a result, digitalization has become imperative for all leading companies. The future belongs to those who can move even faster and are focusing on supply chain optimization technologies to maximize the velocity of doing business.

Disruptions in the supply chain are speed bumps and some are roadblocks. They are not going to go away. If anything, they are getting larger and more frequent. To this end, supply chains need to be designed in a way that can operate smoothly despite the speed bumps. This implies having the ability to see the roadblocks and speed bumps before you get to them. There are two alternatives, predict where they are and/or know how to manage them and respond to their presence. Both are needed, but obviously anticipating them is a lot more efficient. Current use of S&OP systems, as popular as they are, suffers from time and data latency. They are too slow for continuous monitoring and planning as well as their ability to predict what may go wrong. Their rough modeling capability lacks accuracy needed to predict issues resulting in unreliable commit dates and inaccurate financial projections. Furthermore, given the frequency of events and data, coming from both internal operations and external sources, current approach has major limitations.

Consider, for example, the frequency of weather-related issues such as tornados and extreme winter freezes. Companies that are dependent on these regions for their supply have the option of dual sourcing to avoid supply shortages. For those who do not have that choice, they can have systems that can predict the likelihood of the events using predictive techniques that show the likelihood of the event. In addition, companies can have the capability to monitor real-time events in order to immediately re-plan to maximize their production and ensure smooth operations.

Above capabilities are possible by embedding machine learning techniques in a true digital twin of the supply chain to be able to predict, respond and learn from experiences constantly. Optimizing your supply chain technologies can predict the many underlying events in the supply chain that are tell-tale signs of disruptions such as gradual changes in demand, recurring supplier delays, key equipment failures, or abrupt changes in the buyer behavior.

In the absence of continuous planning, every plan is obsolete before it is even executed. Customers want reliable and accurate answers in real-time. Companies need to respond in real-time and be prepared for what is predictable. Most high-frequency and low-impact events are indeed predictable. The opposite, such as Covid-19 or blockage of the Suez Canal may not be. However, with a true digital representation of the supply chain, using an S&OE augmented planning system, the alternatives are immediately apparent to make the right decisions and to maneuver around the disruptions.

In summary, systems are intended to increase the velocity of doing business. Given the large amount of data that are currently available to supply chains, it is imperative that they can sense the data, measure the impact and respond effectively while learning from their experiences. This is why so many companies are optimizing their supply chain technologies. And this is what supply chain 4.0 is all about: big data and intelligence. Learn more about how a continuum of S&OP and S&OE can help you to keep increasing the velocity of your supply chain at Adexa.

The current S&OP systems are too slow for continuous monitoring and planning as well as their ability to predict what may go wrong